Abstract 407: Novel targets in metastatic HNSCC
Notice bibliographique
Résumé
Abstract Head and neck carcinoma (HNSCC) is 6th most common malignancy in the world. Despite advances in diagnosis and treatment, the survival rates remain low due in large part to metastatic disease. The underlying biology associated with metastatic disease and poor outcome in HNSCC remains unclear. Importantly, metastatic cells acquire new properties that permit them to invade surrounding tissues and seed metastasis at distant sites. While these acquired properties contribute to aggressiveness of metastatic cancer and interfere with success of therapies, they can also potentially be exploited to target metastatic cells selectively, sparing toxicity in normal tissues. The idea behind this selective targeting is based on discovering molecular pathways that became essential in metastatic cells, and then exploiting this vulnerability through targeted agents. We used functional genomic technologies to identify new potential therapeutic targets for advanced disease in HNSCC. These targets were identified by conducting whole genome shRNA screens in matched sets of cell lines derived from primary tumors and their respective metastatic sites, with the goal of identifying genes that become essential for cell survival only following metastasis. Since hypoxia is an important attribute of aggressive and therapy resistant subpopulations of HNSCC tumor cells, we also aimed to identify genes that became essential when cells are exposed to hypoxia. To complement the functional screens data, we performed targeted sequencing of the most commonly altered genes in HNSCC as reported by the TCGA profiled gene expression in the HNSCC cell lines cultured under normoxia and hypoxia using Illumina microarrays. These analyses led to the discovery of genes that are differentially essential in metastatic cells as well as in cells exposed to hypoxic conditions. Utilizing CRISPR technology, we assembled a library of guide RNAs targeting the discovered hits and are currently validating the top identified genes using both in vitro and in vivo systems. To validate hits that are essential in metastatic cells in vivo, we engineered selected “matched” pairs of HNSCC cell lines to express CAS9 protein upon induction with doxycycline. The cells are then transduced with the library of guides and injected subcutaneously into mice; tumors from control and doxycycline treated animals are compared. The difference in genes that are essential for growth of tumors seeded by primary tumor derived and metastasis derived HNSCC cell lines is then assessed in a quantitative manner. Citation Format: Maria Kondratyev, Aleksandra Pesic, Troy Ketela, Azin Sayad, Stephano Marastoni, Jason Mofat, Carl Virtanen, Natalie Stickle, Reider Grenman, Brad Wouters. Novel targets in metastatic HNSCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 407.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».